This week, you are learning about the hypothesis testing method in statistics. This process starts by stating the null and alternative hypotheses. Review the terms in "The Visual Learner: Statistics," located in Topic 3 Resources, to answer these questions. 

Think of a research study that you would like to conduct at your current or future place of employment. In designing your research question, describe the null and alternative hypotheses.

What would Type I and II errors look like in this hypothetical situation? Identify if this was a one-tailed or a two-tailed test. 

Initial discussion question posts should be a minimum of 200 words and cite at least two references using APA style. 

Example: 

Impact of a Nature View on Patient Recovery

Research Study: You hypothesize that patients recovering in hospital rooms with a view of nature will recover faster than those in rooms without such a view. 

Null Hypothesis (H₀): The presence of a view of nature in a hospital room has no effect on the recovery time of patients. 

Alternative Hypothesis (H₁): The presence of a view of nature in a hospital room reduces the recovery time of patients. 

Type I Error: A Type I error would occur if the data suggested that a view of nature reduces recovery time when, in reality, it does not. For example, a patient recovery might be better despite the room they are in, yet researchers conclude it was the room location as the causal factory for rapid recovery. 

Type II Error: A Type II error would occur if the data suggested that a view of nature has no effect on recovery time when, in fact, it does. For example, insufficient sample size or improper sampling might not show the recovery time was better than chance alone, concluding the nature view rooms do not have an impact, and are not important for patient recovery.  

One- or Two-Tailed Test: This is a one-tailed test because the hypothesis predicts a specific direction of effect (reduced recovery time) rather than any change in recovery time (increase or decrease). 

Reference
Ulrich, R. S. (1984). View through a window may influence recovery from surgery. The Center for Health Design. https://www-jstor-org.lopes.idm.oclc.org/stable/1692984